Database agnostic SQL exporter for Prometheus
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Database agnostic SQL exporter for Prometheus.
SQL Exporter is a configuration driven exporter that exposes metrics gathered from DBMSs, for use by the Prometheus monitoring system. Out of the box, it provides support for MySQL, PostgreSQL, Microsoft SQL Server and Clickhouse, but any DBMS for which a Go driver is available may be monitored after rebuilding the binary with the DBMS driver included.
The collected metrics and the queries that produce them are entirely configuration defined. SQL queries are grouped into collectors -- logical groups of queries, e.g. query stats or I/O stats, mapped to the metrics they populate. Collectors may be DBMS-specific (e.g. MySQL InnoDB stats) or custom, deployment specific (e.g. pricing data freshness). This means you can quickly and easily set up custom collectors to measure data quality, whatever that might mean in your specific case.
Per the Prometheus philosophy, scrapes are synchronous (metrics are collected on every
/metricspoll) but, in order to keep load at reasonable levels, minimum collection intervals may optionally be set per collector, producing cached metrics when queried more frequently than the configured interval.
$ go install github.com/free/sql_exporter/cmd/sql_exporter
then run it from the command line:
-helpflag to get help information.
$ ./sql_exporter -help Usage of ./sql_exporter: -config.file string SQL Exporter configuration file name. (default "sql_exporter.yml") -web.listen-address string Address to listen on for web interface and telemetry. (default ":9399") -web.metrics-path string Path under which to expose metrics. (default "/metrics") [...]
SQL Exporter is deployed alongside the DB server it collects metrics from. If both the exporter and the DB server are on the same host, they will share the same failure domain: they will usually be either both up and running or both down. When the database is unreachable,
/metricsresponds with HTTP code 500 Internal Server Error, causing Prometheus to record
up=0for that scrape. Only metrics defined by collectors are exported on the
/metricsendpoint. SQL Exporter process metrics are exported at
examplesdirectory. You may contribute your own collector definitions and metric additions if you think they could be more widely useful, even if they are merely different takes on already covered DBMSs.
# Global settings and defaults. global: # Subtracted from Prometheus' scrape_timeout to give us some headroom and prevent Prometheus from # timing out first. scrape_timeout_offset: 500ms # Minimum interval between collector runs: by default (0s) collectors are executed on every scrape. min_interval: 0s # Maximum number of open connections to any one target. Metric queries will run concurrently on # multiple connections. max_connections: 3 # Maximum number of idle connections to any one target. max_idle_connections: 3
The target to monitor and the list of collectors to execute on it.
Data source name always has a URI schema that matches the driver name. In some cases (e.g. MySQL)
the schema gets dropped or replaced to match the driver expected DSN format.
data_source_name: 'sqlserver://prom_user:[email protected]:1433'
Collectors (referenced by name) to execute on the target.
Collector definition files.
Collectors may be defined inline, in the exporter configuration file, under
collectors, or they may be defined in separate files and referenced in the exporter configuration by name, making them easy to share and reuse.
The collector definition below generates gauge metrics of the form
# This collector will be referenced in the exporter configuration as `pricing_data_freshness`. collector_name: pricing_data_freshness
A Prometheus metric with (optional) additional labels, value and labels populated from one query.
marketcolumn of each row.
To keep things simple and yet allow fully configurable database connections to be set up, SQL Exporter uses DSNs (like
sqlserver://prom_user:[email protected]:1433) to refer to database instances. However, because the Go
sqllibrary does not allow for automatic driver selection based on the DSN (i.e. an explicit driver name must be specified) SQL Exporter uses the schema part of the DSN (the part before the
://) to determine which driver to use.
tcp://. So SQL Exporter does a bit of massaging of DSNs for the latter two drivers in order for this to work:
|SQL Exporter expected DSN||Driver sees|
SQL Exporter started off as an exporter for Microsoft SQL Server, for which no reliable exporters exist. But what is the point of a configuration driven SQL exporter, if you're going to use it along with 2 more exporters with wholly different world views and configurations, because you also have MySQL and PostgreSQL instances to monitor?
A couple of alternative database agnostic exporters are available -- https://github.com/justwatchcom/sql_exporter and https://github.com/chop-dbhi/prometheus-sql -- but they both do the collection at fixed intervals, independent of Prometheus scrapes. This is partly a philosophical issue, but practical issues are not all that difficult to imagine: jitter; duplicate data points; or collected but not scraped data points. The control they provide over which labels get applied is limited, and the base label set spammy. And finally, configurations are not easily reused without copy-pasting and editing across jobs and instances.